Screening of key genes associated with R‑CHOP immunochemotherapy and construction of a prognostic risk model in diffuse large B‑cell lymphoma

Abstract

Diffuse large B-cell lymphoma (DLBCL) is a common subtype of non-Hodgkin lymphoma, which is curable in the majority of patients treated with rituximab plus cyclophosphamide, doxorubicin, vincristine and prednisone (R-CHOP) immunochemotherapy. However, the therapeutic mechanism of R-CHOP has not been elucidated. The GSE32918 and GSE57611 datasets were retrieved from The Gene Expression Omnibus database. The differentially expressed genes (DEGs) associated with R-CHOP therapy were identified using limma. Combined with prognostic information in GSE32918, DEGs found to be significantly associated with prognosis were selected using univariate Cox regression analysis and a risk prediction model was constructed. Based on this model, the samples in the training set (GSE32918) were divided into high and low risk score groups according to the median risk score. A total of 801 DEGs were identified between the R-CHOP treated DLBCL and primary DLBCL samples, from this 116 prognosis-associated genes were selected. Using Cox proportional hazards model, an optimal combination of 12 genes [including calcium/calmodulin dependent protein kinase I (CAMK1), hippocalcin like 4 (HPCAL4) and ephrin A5 (EFNA5)] was selected, and the sample risk score prediction model was constructed and validated. The DEGs between high risk score and low risk score groups were significantly enriched in functions associated with ‘response to DNA damage stimulus’, and pathways including ‘cytokine-cytokine receptor interaction’ and ‘cell cycle’. The optimal combination of the 12 genes, including CAMK1, HPCAL4 and EFNA5, was found to be useful in predicting the prognosis of patients with DLBCL after R-CHOP treatment. Therefore, these genes may be affected by R-CHOP in DLBCL.

Baseline tumor gene expression signatures correlate with chemoimmunotherapy treatment responsiveness in canine B cell lymphoma

“…However, not all immune signatures studied have found significant biologic correlates, supporting the notion that a better understanding of the immune micro environment is necessary to validate prognostic biomarkers associated with response to therapy [ 4 ]. Finally, the variability in predictive potential of gene expression panels also suggests that the genetic context of these gene expression patterns are important determinates of response both in the immune system and the tumor itself [ 8 , 9 ].…”

“…Several human DLBCL studies have created gene signature panels incorporating tumor microenvironment-related genes that predict survival [6][7][8]. For example, Merdan et al performed RNA-sequencing on tumor samples and gene expression analysis using edgeR package to create gene expression-based scores that were associated with long-term survival [6].…”

SCADIE: simultaneous estimation of cell type proportions and cell type-specific gene expressions using SCAD-based iterative estimating procedure

“…Diffuse large B cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma and can be classified into two main subtypes based on gene expression: germinal center-like (GCB) and activated B cell-like (ABC) DLBCL [ 2 , 19 ]. Traditionally DLBCL patients were treated with cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP), and in recent years CHOP in combination with immunotherapeutic drug rituximab (R-CHOP) has gained more popularity due to its benefit in clinical outcome [ 33 ].…”

Sufficient principal component regression for pattern discovery in transcriptomic data

“…CORO1A encodes the actin-binding tumor suppressor p57/coronin-1a, the promoter of which is often hypermethylated, and therefore likely silenced in DLBCL ( Li et al , 2002 ). FEZ1 expression has been used in a prognostic model ( Liu et al , 2019 ). RAG1 , encoding a protein involved in generating antibody diversity, can induce specific genetic aberrations found in DLBCL ( Miao et al , 2019 ).…”